Detection of a leading stroke risk indicator

Abstract

Embodiments of a system and method for detecting a leading stroke risk indicator using low-cost, non-contact visual computing methods are generally described herein. In some embodiments, a video camera is arranged to capture a video of a face of a subject to be evaluated for having a stroke risk indicator. A memory is provided for storing data. A processor is coupled to the memory and is arranged to analyze processed image data associated with the video of the face of the subject captured by the video camera. The processor is further arranged to determine whether the processed image data exhibits a leading indicator for carotid artery stenosis.

What is claimed is: 
     
       1. A device for detecting a leading stroke risk indicator, comprising:
 a video camera configured to capture a video of a face of a subject to be evaluated for having a stroke risk indicator; 
 a memory for storing the video; and 
 a processor, coupled to the memory, the processor configured to:
 process the video to produce a first pulse waveform associated with a pulse of a right side of the face of the subject and to produce a second pulse waveform associated with a pulse of a left side of the face of the subject; 
 identify a peak of the first pulse waveform and identify a peak of the second pulse waveform; 
 analyze the first and second pulse waveforms to measure a phase shift between the peak of the first pulse waveform and the peak of the second pulse waveform; and 
 determine whether the subject exhibits a leading indicator for carotid artery stenosis based on the phase shift. 
 
 
     
     
       2. The device of  claim 1 , the processor comprising a local video processing device configured to perform image processing of the video to produce the first and second pulse waveforms. 
     
     
       3. The device of  claim 1  further comprising a transceiver, the transceiver configured to forward the video to the processor, the processor comprising a remote video processing device, the remote video processing device to perform image processing of the forwarded video to produce the first and second pulse waveforms. 
     
     
       4. The device of  claim 1 , wherein the processor is configured to determine the leading indicator for carotid artery stenosis is exhibited when the phase shift exceeds a predetermined value. 
     
     
       5. The device of  claim 1 , wherein the first and second pulse waveforms are processed by the processor to cross-correlate the first and second pulse waveforms to measure the phase shift. 
     
     
       6. The device of  claim 1 , wherein the video camera provides video data to a remote user via a video communications module. 
     
     
       7. The device of  claim 6  further comprising a speaker, wherein the remote user uses the provided video data to provide audio instructions to the subject via the speaker. 
     
     
       8. A method fur detecting a leading stroke risk indicator, comprising:
 capturing, at a video capture device, a video of a face of a subject; 
 processing, by a video image processor, the video to produce a first pulse waveform associated with a pulse of a right side of the face of the subject and to produce a second pulse waveform associated with a pulse of a left side of the face of the subject; 
 identifying a peak of the first pulse waveform and a peak of the second pulse waveform; 
 analyzing the first and second pulse waveforms to measure a phase shift between the peak of the first pulse waveform and the peak of the second pulse waveform; and 
 determining whether the subject exhibits a leading indicator for carotid artery stenosis based on the phase shift; and 
 generating a report indicating stenosis risk is detected and suggesting the subject visit a doctor for verification when the analysis of the first and second pulse waveforms determines that the subject exhibits the leading indicator for carotid artery stenosis. 
 
     
     
       9. The method of  claim 8 , the processing comprising performing, local to the subject, image processing of the captured video to produce the first and second waveforms. 
     
     
       10. The method of  claim 8  further comprising transmitting, from the video capture device, the video to a remote video processing device;
 wherein the processing comprises performing image processing of the captured video of the face of the subject at the remote video processing device to produce the first and second pulse waveforms. 
 
     
     
       11. The method of  claim 8  further comprising storing the captured video in memory at the video capture device. 
     
     
       12. The method of  claim 8 , further comprising determining the leading indicator for carotid artery stenosis is exhibited when the phase shift exceeds a predetermined value. 
     
     
       13. The method of  claim 8 , further comprising processing the first and second pulse waveforms to cross-correlate the first pulse waveform with the second pulse waveform to measure the phase shift. 
     
     
       14. The method of  claim 8  further comprising providing video data from the video capture device to a remote user via a video communications module and providing audio instructions to the subject via a speaker based on the video data provided to the remote user via the video communications module. 
     
     
       15. At least one non-transitory machine readable medium comprising instructions that, when executed by the machine, cause the machine to perform operations for detecting a leading stroke risk indicator, the operations comprising:
 capturing, at a video capture device, a video of a face of a subject; 
 processing, by a video image processor, the video of the face of the subject to produce a first pulse waveform associated with a pulse of a right side of the face of the subject and to produce a second pulse waveform associated with a pulse of a left side of the face of the subject; 
 identifying a peak of the first pulse waveform and a peak of the second pulse waveform; 
 analyzing the first and second pulse waveforms to measure a phase shift between the peak of the first pulse waveform and the peak of the second pulse waveform; and 
 determining whether the subject exhibits a leading indicator for carotid artery stenosis based on the phase shift; and 
 generating a report indicating stenosis risk is detected and suggesting the subject visit a doctor for verification when the analysis of the first and second pulse waveforms determines that the subject exhibits the leading indicator for carotid artery stenosis. 
 
     
     
       16. The at least one non-transitory machine readable medium of  claim 15 , the processing comprising performing, local to the subject, image processing of the captured video to produce the first and second waveforms. 
     
     
       17. The at least one non-transitory machine readable medium of  claim 15  further comprising transmitting, from the video capture device, the video to a remote video processing device;
 wherein the processing comprises performing image processing of the captured video of the face of the subject at the remote video processing device to produce the first and second pulse waveforms. 
 
     
     
       18. The at least one non-transitory machine readable medium of  claim 15 , the operations further comprising determining the leading indicator for carotid artery stenosis is exhibited when the phase shift exceeds a predetermined value. 
     
     
       19. The at least one non-transitory machine readable medium of  claim 15 , the operations further comprising processing the first and second pulse waveforms to cross-correlate the first pulse waveform with the second pulse waveform to measure the phase shift. 
     
     
       20. The at least one non-transitory machine readable medium of  claim 15  further comprising providing video data from the video capture device to a remote user via a video communications module and providing audio instructions to the subject via a speaker based on the video data provided to the remote user via the video communications module.